class_docstr: Implementation of the model H/ASP without batch normalization in speaker embedding. This model was proposed in: https://arxiv.org/abs/2009.14153
  Adapted from: https://github.com/clovaai/voxceleb_trainer
class_docstr_tok: ["Implementation","of","the","model","H\/ASP","without","batch","normalization","in","speaker","embedding",".","This","model","was","proposed","in",":","https",":","\/\/arxiv.org\/abs\/2009.14153","Adapted","from",":","https",":","\/\/github.com\/clovaai\/voxceleb_trainer"]
code: def _init_layers(self):
      for m in self.modules():
          if isinstance(m, nn.Conv2d):
              nn.init.kaiming_normal_(
                  m.weight, mode="fan_out", nonlinearity="relu"
              )
          elif isinstance(m, nn.BatchNorm2d):
              nn.init.constant_(m.weight, 1)
              nn.init.constant_(m.bias, 0)
  
file_path: TTS/TTS/encoder/models/resnet.py
imports: import torch
  from torch import nn
  from TTS.encoder.models.base_encoder import BaseEncoder
label_desc: Use image node_id 2 for calling the ResNetSpeakerEncoder obj's underlying member method code with example usage: obj._init_layers() without return types